Meta Description: HR tech trends are tilted in favor of AI adoption. 2020 will see HR embracing AI even more. Here’s how AI in HR is transforming candidate screening to employee experience; everything.
2020 will be the year human resources embrace AI technologies. From sourcing and screening of candidates to recruitment and augmenting employee experience, AI has the potential to automate HR processes.
One reflecting on AI adoption in HR cannot help but wonder – what will a department of human resources look like with machines doing their tasks?
Speculations run rife as AI in HR reach two-pronged paths – AI will replace or collaborate with human resource professionals. A TOPCHRO report on “Opportunities and Challenges in AI Inclusion” shows, the image of AI technologies is prominent as a collaborative tool among employers. 96% of recruiters believe AI will bring next big revolution in talent acquisition. It further states,
Today, 100% of the sourcing, screening and matching functions, and 20% of hiring manager and candidate relations, in HR can be automated.
Here we discuss the major highlights of HR tech trends in adoption of AI. You can access the full report below. Before that, let’s get our basics in order and briefly reflect on how two branches of AI – Machine learning and deep learning enables machines think like humans and its use cases in HR.
Machine and Deep Learning in HR
- Machine Learning & Use Cases in HR
Machine Learning enables machines to learn from data and make predictions. The idea is that algorithms can learn without being programmed for every task. It is embedded in pattern recognition.
Talk Layman: Think of cars. To identify a car, an AI algorithm can rely on several images of cars to teach itself how a car looks like. This is called Machine Learning. In here, you are stating the end objective that you need a car to be identified. Now, how the program arrives at those objectives is learned by the machine itself via past data.
Use Cases and Examples: ML in HR tech can be used for anomaly detection, background verification, employee attrition, content personalization.
- Deep Learning & Use Cases in HR
Deep learning is an advanced branch of machine learning. It breaks data in layers and instead of organizing data in preset equations, it sets overall parameters, within which the program trains the computer to learn on its own by pattern recognition using multiple neural network layers (just like neurons in our brain).
Talk Layman: Taking the car from previous example, while Machine learning can teach machines to recognize a car; Deep learning will enable a machine to differentiate between a car and truck by identifying core elements.
Use Cases and Examples: Par HR tech trends, deep learning can be used for image and video recognition, speech recognition, chatbots, and making personalized recommendations.
Highlights of the report – Opportunities and Challenges of AI inclusion in HR
- Most applicants do not fit the requirements and screening those candidates wastes about 1.5 working days HR professionals every week. Report shows over 75 to 85% of the resumes do not fit the bill in recruitment, and this leads to throwing away 14 hours per week for no results to account for.
- Talent acquisition experts say screening candidates is the most difficult and time-consuming part of their job. 52% of the talent acquisition leaders pointed that screening candidates is the hardest part of recruitment.
- Not deploying AI in HR leads to underperforming teams and lost opportunities. It lowers productivity by 41%, increases cost by 35%, and reduces candidate experience by 17%.
- Using AI in HR technology reduces three fourth costs of candidate screening and decreases employee attrition almost by half.
Check the detailed case study in the report on how Unilever, an industry giant in FMCG, transformed its HR process with AI. Download the report here.
